Serena Low1,2, Kay Chin Jonathon Khoo2, Jiexun Wang2, Bastari Irwan3, Chee Fang Sum1, Tavintharan Subramaniam1, Su Chi Lim4,5,6, Tack Keong Michael Wong7. 1. Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore. 2. Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore. 3. Transformation Office, Hospital Administration, Khoo Teck Puat Hospital, Singapore, Singapore. 4. Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore. lim.su.chi@ktph.com.sg. 5. Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore. lim.su.chi@ktph.com.sg. 6. Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. lim.su.chi@ktph.com.sg. 7. Family and Community Medicine, Khoo Teck Puat Hospital, Singapore, Singapore.
Abstract
PURPOSE: Metabolic syndrome (MetS) is a constellation of clinical factors that indicates elevated risk of diabetes. It is diagnosed based on three or more abnormalities in its components. This does not take into account that MetS can likely present as a continuum of risk. We aim to develop a MetS severity score and assess its association with incident diabetes. METHODS: In total, 4149 subjects without baseline diabetes participated in a community screening programme in 2013-2017. MetS was defined according to International Diabetes Federation criteria. A MetS severity z-score was derived from standardised loading coefficients of a confirmatory factor analysis for waist circumference, triglycerides, HDL-cholesterol, blood pressure and fasting plasma glucose (FPG). Multivariable cox proportional hazards regression model was used to assess the risk of diabetes by the score with adjustment for demographics and MetS components. RESULTS: Diabetes occurred in 130 subjects. Quintile 5 of the baseline MetS severity z-score was significantly associated with development of diabetes even in fully adjusted model with HR 2.63 (95% CI: 1.04-6.64; p = 0.040). The relationship between MetS and incident diabetes became attenuated and non-significant in fully adjusted model with HR 0.67 (95% CI: 0.34-1.29; p = 0.228). Mediation analysis showed that MetS severity z-score accounted 61.0% of the association between increasing body mass index and development of diabetes (p < 0.001). CONCLUSIONS: The MetS severity z-score is an inexpensive and clinically-available continuous measure of MetS to identify individuals at high risk of diabetes.
PURPOSE:Metabolic syndrome (MetS) is a constellation of clinical factors that indicates elevated risk of diabetes. It is diagnosed based on three or more abnormalities in its components. This does not take into account that MetS can likely present as a continuum of risk. We aim to develop a MetS severity score and assess its association with incident diabetes. METHODS: In total, 4149 subjects without baseline diabetes participated in a community screening programme in 2013-2017. MetS was defined according to International Diabetes Federation criteria. A MetS severity z-score was derived from standardised loading coefficients of a confirmatory factor analysis for waist circumference, triglycerides, HDL-cholesterol, blood pressure and fasting plasma glucose (FPG). Multivariable cox proportional hazards regression model was used to assess the risk of diabetes by the score with adjustment for demographics and MetS components. RESULTS:Diabetes occurred in 130 subjects. Quintile 5 of the baseline MetS severity z-score was significantly associated with development of diabetes even in fully adjusted model with HR 2.63 (95% CI: 1.04-6.64; p = 0.040). The relationship between MetS and incident diabetes became attenuated and non-significant in fully adjusted model with HR 0.67 (95% CI: 0.34-1.29; p = 0.228). Mediation analysis showed that MetS severity z-score accounted 61.0% of the association between increasing body mass index and development of diabetes (p < 0.001). CONCLUSIONS: The MetS severity z-score is an inexpensive and clinically-available continuous measure of MetS to identify individuals at high risk of diabetes.
Authors: Maria Inês Schmidt; Bruce B Duncan; Heejung Bang; James S Pankow; Christie M Ballantyne; Sherita H Golden; Aaron R Folsom; Lloyd E Chambless Journal: Diabetes Care Date: 2005-08 Impact factor: 19.112
Authors: Matthew J Gurka; Sherita H Golden; Solomon K Musani; Mario Sims; Abhishek Vishnu; Yi Guo; Michelle Cardel; Thomas A Pearson; Mark D DeBoer Journal: Diabetologia Date: 2017-04-04 Impact factor: 10.122
Authors: Jennifer K Gustafson; Lisa B Yanoff; Benjamin D Easter; Sheila M Brady; Margaret F Keil; Mary D Roberts; Nancy G Sebring; Joan C Han; Susan Z Yanovski; Van S Hubbard; Jack A Yanovski Journal: J Clin Endocrinol Metab Date: 2009-10-16 Impact factor: 5.958